Machine Learning And Perception
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Deep Learning For Robot Perception And Cognition
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Author : Alexandros Iosifidis
language : en
Publisher: Academic Press
Release Date : 2022-02-04
Deep Learning For Robot Perception And Cognition written by Alexandros Iosifidis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-04 with Technology & Engineering categories.
Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis
Machine Learning And Perception
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Author : Guido Tascini
language : en
Publisher: World Scientific
Release Date : 1996-05-06
Machine Learning And Perception written by Guido Tascini and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-05-06 with categories.
The present well-established study of planets orbiting stars other than our Sun, the exoplanets, was reviewed by the author in his earlier book Wandering Stars. This new and exciting field of study has expanded quickly, particularly due to technological advances in both Earth-based telescopes and, more recently, in the application of automatic space vehicles. Well over 300 exoplanets have now been catalogued, each of mass comparable to or greater than those of the major planets of the Solar System. Earth-sized bodies remain out of reach for the present. The data obtained so far show that the distribution of major planets in our Solar System is the exception rather than the rule, contrary to earlier expectations. A few exoplanet systems do, nevertheless, give the promise of broadly Solar System conditions with the possibility of Earth-like components in appropriate orbits.This immediately raises the age-old question of whether there can be life elsewhere in the Universe and whether this might involve advanced technologically-capable beings like ourselves. The topic is explored in this workbook. To gain a balanced perspective on these matters, the arguments are set against the broad panorama of the Universe on the one hand and on the evolution of life on Earth leading to Homo sapiens on the other. More than this, the apparatus for achieving technological excellence, such as the development of appropriate energy sources and the invention of the required mathematical skills, is also included. This wide range of arguments is unusual.This notebook-cum-workbook provides a firm and comprehensive introduction to these studies. It is written by an expert in the field for readers beginning to ponder these questions seriously. It is hoped that the reader will extend the arguments further as the subject develops. A special feature is an extensive compendium to act as the beginnings of a personal inventory. The Inverted Bowl is in a very real sense a companion to Wandering Stars./a
Machine Learning And Visual Perception
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Author : Baochang Zhang
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2020-07-06
Machine Learning And Visual Perception written by Baochang Zhang and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-06 with Computers categories.
The book provides an up-to-date on machine learning and visual perception, including decision tree, Bayesian learning, support vector machine, AdaBoost, object detection, compressive sensing, deep learning, and reinforcement learning. Both classic and novel algorithms are introduced. With abundant practical examples, it is an essential reference to students, lecturers, professionals, and any interested lay readers.
Machine Learning A Journey To Deep Learning With Exercises And Answers
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Author : Andreas Miroslaus Wichert
language : en
Publisher: World Scientific
Release Date : 2021-01-26
Machine Learning A Journey To Deep Learning With Exercises And Answers written by Andreas Miroslaus Wichert and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-26 with Computers categories.
This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)
Hidden Markov Models Applications In Computer Vision
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Author : Horst Bunke
language : en
Publisher: World Scientific
Release Date : 2001-06-04
Hidden Markov Models Applications In Computer Vision written by Horst Bunke and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-06-04 with Computers categories.
Hidden Markov models (HMMs) originally emerged in the domain of speech recognition. In recent years, they have attracted growing interest in the area of computer vision as well. This book is a collection of articles on new developments in the theory of HMMs and their application in computer vision. It addresses topics such as handwriting recognition, shape recognition, face and gesture recognition, tracking, and image database retrieval.This book is also published as a special issue of the International Journal of Pattern Recognition and Artificial Intelligence (February 2001).
Analogy Making As Perception
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Author : Melanie Mitchell
language : en
Publisher: Bradford Book
Release Date : 1993
Analogy Making As Perception written by Melanie Mitchell and has been published by Bradford Book this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Analogy categories.
The psychologist William James observed that "a native talent for perceiving analogies is... the leading fact in genius of every order." The centrality and the ubiquity of analogy in creative thought have been noted again and again by scientists, artists, and writers, and understanding and modeling analogical thought have emerged as two of the most important challenges for cognitive science.Analogy-Making as Perception is based on the premise that analogy-making is fundamentally a high-level perceptual process in which the interaction of perception and concepts gives rise to "conceptual slippages" which allow analogies to be made. It describes Copycat - a computer model of analogymaking, developed by the author with Douglas Hofstadter, that models the complex, subconscious interaction between perception and concepts that underlies the creation of analogies.In Copycat, both concepts and high-level perception are emergent phenomena, arising from large numbers of low-level, parallel, non-deterministic activities. In the spectrum of cognitive modeling approaches, Copycat occupies a unique intermediate position between symbolic systems and connectionist systems a position that is at present the most useful one for understanding the fluidity of concepts and high-level perception.On one level the work described here is about analogy-making, but on another level it is about cognition in general. It explores such issues as the nature of concepts and perception and the emergence of highly flexible concepts from a lower-level "subcognitive" substrate.Melanie Mitchell, Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, is a Fellow of the Michigan Society of Fellows. She is also Director of the Adaptive Computation Program at the Santa Fe Institute.
Practical Machine Learning For Computer Vision
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Author : Valliappa Lakshmanan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-07-21
Practical Machine Learning For Computer Vision written by Valliappa Lakshmanan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-21 with Computers categories.
This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model Preprocess images for data augmentation and to support learnability Incorporate explainability and responsible AI best practices Deploy image models as web services or on edge devices Monitor and manage ML models
Understanding Machine Learning
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Author : Shai Shalev-Shwartz
language : en
Publisher: Cambridge University Press
Release Date : 2014-05-19
Understanding Machine Learning written by Shai Shalev-Shwartz and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-19 with Computers categories.
Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Python For Machine Learning And Natural Language Processing In Robotics And Autonomous Vehicles
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Author : Mr. Akash Arun Kumar Soumya
language : en
Publisher: BUDHA PUBLICATION
Release Date :
Python For Machine Learning And Natural Language Processing In Robotics And Autonomous Vehicles written by Mr. Akash Arun Kumar Soumya and has been published by BUDHA PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
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Spoken Language Understanding
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Author : Gokhan Tur
language : en
Publisher: John Wiley & Sons
Release Date : 2011-05-03
Spoken Language Understanding written by Gokhan Tur and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-03 with Language Arts & Disciplines categories.
Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, using differing tasks and approaches to better understand and utilize such communications. This book covers the state-of-the-art approaches for the most popular SLU tasks with chapters written by well-known researchers in the respective fields. Key features include: Presents a fully integrated view of the two distinct disciplines of speech processing and language processing for SLU tasks. Defines what is possible today for SLU as an enabling technology for enterprise (e.g., customer care centers or company meetings), and consumer (e.g., entertainment, mobile, car, robot, or smart environments) applications and outlines the key research areas. Provides a unique source of distilled information on methods for computer modeling of semantic information in human/machine and human/human conversations. This book can be successfully used for graduate courses in electronics engineering, computer science or computational linguistics. Moreover, technologists interested in processing spoken communications will find it a useful source of collated information of the topic drawn from the two distinct disciplines of speech processing and language processing under the new area of SLU.